Regression

Hi Friends,


Welcome again,

Today We are going to learn about Regression. We have already learn a brief about regression. But now, we take deep dive into the regression. It is a very broad thing in ML.

So, let's start with regression.
Regression is a type of supervised learning, so it has input variable as well as output variable like classification, but regression works for statistical analysis on data. or we can say it is a statistical process  to estimate real values, such  as, prices of different cars.

Lets take an example of regression:

import csv
import numpy
import matplotlib.pyplot as plt
from matplotlib import style
style.use("ggplot")
from sklearn import svm

file_name="regression_ex.csv"

raw_data=open(file_name,"rt")
reader=csv.reader(raw_data,delimiter=',',quoting=csv.QUOTE_NONE)
x=list(reader)
data=numpy.array(x)

plt.scatter(data[1:,0],data[1:,1])

Output:

Figure: Regression of Month wise Heatwave

So, This is a simple example of regression. in next article, we will learn different types of regression.